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	Conformalized temporal convolutional quantile regression networks for wind power interval forecasting 期刊论文 ENERGY, 2022, 卷号: 248, 页码: 16 作者: Hu, Jianming; Luo, Qingxi; Tang, Jingwei; Heng, Jiani; Deng, Yuwen 收藏 \| 浏览/下载：10/0 \| 提交时间：2023/02/07 Wind power interval prediction Temporal convolutional network Conformalized quantile regression
	Wind Speed Short-Term Prediction Based on Empirical Wavelet Transform, Recurrent Neural Network and Error Correction 期刊论文 Journal of Shanghai Jiaotong University (Science), 2022 作者: Zhu, Changsheng; Zhu, Lina 收藏 \| 浏览/下载：16/0 \| 提交时间：2022/08/09 Brain Elman neural networks Error correction Forecasting Multilayer neural networks Speed Stochastic systems Wavelet transforms Wind power Wind speed A Deep long short term memory network Empirical wavelet transform Error correction strategy Errors correction Memory network TM 614 Wavelets transform Wind speed Wind speed prediction
	Deep Learning-Based Prediction of Wind Power for Multi-turbines in a Wind Farm 期刊论文 FRONTIERS IN ENERGY RESEARCH, 2021, 卷号: 9 作者: Chen, Xiaojiao; Zhang, Xiuqing; Dong, Mi; Huang, Liansheng; Guo, Yan 收藏 \| 浏览/下载：22/0 \| 提交时间：2021/09/06 wind farm wind turbine convolutional neural network long short-term memory network spatiotemporal power prediction
	A hybrid method for short-term wind speed forecasting based on Bayesian optimization and error correction 期刊论文 JOURNAL OF RENEWABLE AND SUSTAINABLE ENERGY, 2021, 卷号: 13, 期号: 3 作者: Guo, Xiuting; Zhu, Changsheng; Hao, Jie; Zhang, Shengcai; Zhu, Lina 收藏 \| 浏览/下载：20/0 \| 提交时间：2021/10/14 Error correction Forecasting Machine learning Speed Wavelet transforms Wind power Bayesian optimization algorithms Error correction models Extreme learning machine Hyper-parameter optimizations Large-scale wind power Prediction performance Short-term wind speed forecasting Wind speed prediction
	Wind Power Short-Term Forecasting Model Based on the Hierarchical Output Power and Poisson Re-Sampling Random Forest Algorithm 期刊论文 IEEE Access, 2021, 卷号: 9, 页码: 6478-6487 作者: Hao, Jie; Zhu, Changsheng; Guo, Xiuting 收藏 \| 浏览/下载：20/0 \| 提交时间：2021/03/02 Decision trees Economics Electric power system interconnection Electric utilities Predictive analytics Random forests Statistical tests Weather forecasting Wind power Chi-square tests Classification models Random forest algorithm Real time characteristics Short term prediction Short-term forecasting Short-term wind power forecasting Wind power predictions
	Short-Term Photovoltaic Power Interval Prediction Based on VMD and GOA-KELM Algorithms 会议论文 Chengdu, China, May 7-10, 2021 作者: Sun, Wenxuan; Wang AN(王安娜); Zhang T(张涛) 收藏 \| 浏览/下载：7/0 \| 提交时间：2022/04/23 photovoltaic power prediction variational mode decomposition grasshopper optimization algorithm kernel extreme learning machine interval prediction
	Accurate prediction of short-term photovoltaic power generation via a novel double-input-rule-modules stacked deep fuzzy method 期刊论文 ENERGY, 2020, 卷号: 212, 页码: 13 作者: Li, Chengdong; Zhou, Changgeng; Peng, Wei; Lv, Yisheng; Luo, Xin 收藏 \| 浏览/下载：37/0 \| 提交时间：2021/03/08 PV power generation prediction Deep fuzzy model Double input rule module Data driven method Least square method
	Aeolian Creep Transport: Theory and Experiment 期刊论文 Geophysical Research Letters, 2020, 卷号: 47, 期号: 15 作者: Wang, Peng; Zhang, Jie; Dun, Hongchao; Herrmann, Hans J.; Huang, Ning 收藏 \| 浏览/下载：9/0 \| 提交时间：2020/11/14 Wind tunnels Analytic expressions Geophysical phenomena Layer thickness Power-scaling Quantitative prediction Steady state Transport rate Wind tunnel experiment
	Aeolian Creep Transport: Theory and Experiment 会议论文作者: Wang, Peng; Zhang, Jie; Dun, Hongchao; Herrmann, Hans J.; Huang, Ning 收藏 \| 浏览/下载：5/0 \| 提交时间：2020/12/18 Wind tunnelsAnalytic expressions Geophysical phenomena Layer thickness Power-scaling Quantitative prediction Steady state Transport rate Wind tunnel experiment
	A Prediction Model for Ultra-Short-Term Output Power of Wind Farms Based on Deep Learning 期刊论文 INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, 2020, 卷号: 15, 期号: 4, 页码: 18 作者: Wang, Y. S.; Gao, J.; Xu, Z. W.; Luo, J. D.; Li, L. X. 收藏 \| 浏览/下载：3/0 \| 提交时间：2020/12/10 wind power output power ultra-short-term prediction deep learning (DL) long short-term memory (LSTM) model

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